Decentralized Identity (DID) systems aim to restore user control over digital identities by minimizing reliance on centralized authorities. However, ensuring secure identity management in distributed environments remains a significant challenge. Biometric authentication offers a compelling solution by leveraging unique, non-transferable human traits to enhance security and usability compared to traditional methods such as passwords or tokens. Integrating biometrics into DID frameworks represents an important step toward privacy-preserving, user-centric identity verification aligned with the principles of decentralization. Despite growing interest in both biometrics and DIDs, their integration remains largely underexplored in the literature, with hardly any survey providing a systematic analysis of this convergence. This work addresses this gap by presenting a comprehensive review of biometric-enabled DID systems, examining their architectures, potential, and limitations. It emphasizes the role of multimodal biometrics in enhancing accuracy, inclusiveness, and resistance to spoofing, while highlighting key challenges related to data immutability, privacy preservation, interoperability, and regulatory compliance. Overall, this survey establishes a structured foundation for future research on secure, scalable, and privacy-preserving biometric-enabled decentralized identity frameworks.
Rjab et al. (Mon,) studied this question.